A Go package for using Ollama and large language models (LLMs).

package main

import (
    "fmt"

    "github.com/xyproto/ollamaclient/v2"
)

func main() {
    // Create an Ollama client configuration struct and select a model.
    // The default model is "gemma2:2b". See: https://ollama.com/library/

    //oc := ollamaclient.New("llama3.1:latest")
    //oc := ollamaclient.New("mixtral:instruct")
    //oc := ollamaclient.New("tinyllama:latest")

    oc := ollamaclient.New()

    oc.Verbose = true

    if err := oc.PullIfNeeded(); err != nil {
        fmt.Println("Error:", err)
        return
    }

    prompt := "Write a haiku about the color of cows."
    output, err := oc.GetOutput(prompt)
    if err != nil {
        fmt.Println("Error:", err)
        return
    }
    fmt.Printf("\n%s\n", output)
}

Example output (with verbosity set to true):

Sending request to /api/tags
Sending request to /api/generate: {"model":"mistral:instruct","prompt":"Write a haiku about the color of cows."}

Majestic brown cows
Grazing in green fields so serene
Nature's masterpiece

Make sure to install and run Ollama first, or set OLLAMA_HOST to a valid host.

A simple way to describe images:

package main

import (
    "fmt"
    "log"

    "github.com/xyproto/ollamaclient/v2"
)

func main() {
    oc := ollamaclient.New("llava")
    oc.SetReproducible()
    if err := oc.PullIfNeeded(true); err != nil {
        log.Fatalln(err)
    }
    imageFilenames := []string{"carrot1.png", "carrot2.png"}
    const desiredWordCount = 7
    description, err := oc.DescribeImages(imageFilenames, desiredWordCount)
    if err != nil {
        log.Fatalln(err)
    }
    fmt.Println(description)
}

See v2/cmd/describeimage for an example that uses a custom prompt.

• The .Embeddings method can be used to pass in a prompt and return a []float64.

These environment variables are supported:

• OLLAMA_HOST (http://localhost:11434 by default)
• OLLAMA_MODEL (llama3.1:latest by default)
• OLLAMA_VERBOSE (false by default)

Getting started:

1. Install ollama and start it as a service.
2. Run ollama pull llama3.1:latest to fetch the llama3.1:latest model.
3. Install the summarize utility: go install github.com/xyproto/ollamaclient/cmd/summarize@latest
4. Summarize a README.md file and a source code file: summarize README.md ollamaclient.go
5. Write a poem about one or more files: summarize --prompt "Write a poem about the following files:" README.md

Usage:

./summarize [flags] <filename1> [<filename2> ...]

Flags:

• -m, --model: Specify an Ollama model. The default is llama3.1:latest.
• -o, --output: Define an output file to store the summary.
• -p, --prompt: Specify a custom prompt header for summary. The default is Write a short summary of a project that contains the following files:
• -w, --wrap: Set the word wrap width. Use -1 to detect the terminal width.
• -v, --version: Display the current version.
• -V, --verbose: Enable verbose logging.

Generate a summary with a custom prompt:

./summarize -w -1 -p "Summarize these files:" README.md CONFIG.md

Generate a summary, saving the output to a file:

./summarize -o output.txt README.md CONFIG.md

Generate a summary with custom word wrap width:

./summarize -w 100 README.md

go test depends on a local Ollama server being up and running, and will attempt to download the llama3.1, llava and gemma2:2b models.

• Version: 2.5.0
• License: Apache 2